A study on the number of principal components and sensitivity of fault detection using PCA

Abstract

Selection of the number of principal components (PC) in the fault detection method using principal component analysis (PCA) is considered. In this paper, we focus on the relationship between the sensitivity of fault detection and the number of PCs to retain. Consideration of the signal-to-noise ratio of fault detection (Fault SNR) is proposed. The Fault SNR shows different dependency on the number of PCs for different kinds of faults. The number of PCs that gives the maximum sensitivity is easily determined for sensor faults by examining the Fault SNR. If a priori data is available, that is, operation data measured during faulty conditions, optimization of the number of PCs for the process fault is also possible. In a case where a priori information of the fault is not available, monitoring multiple models with various numbers of PCs in parallel is considered the next best strategy.